A hierarchical logistic regression model is proposed for studying data with group structure and a binary response variable. The group structure is defined by the presence of micro observations ...

This book also explains the differences and similarities between the many generalizations of the logistic regression model. The following topics are covered: binary logit analysis, logit analysis of ...

Because many common DIF detection methods ignore potential DIF variance, this paper proposes the use of random coefficient hierarchical logistic regression (RC-HLR) models to test for both uniform DIF ...

In addition, PROC GLM allows only one model and fits the full model. See Chapter 4, "Introduction to Analysis-of-Variance Procedures," and Chapter 30, "The GLM Procedure," for more details. The CATMOD ...

When applied to the study data, we obtain a ranking of models that differs from those based on AIC and MSEP, as well as a tree-based method and regularized logistic regression using a lasso penalty.